Author:
Zhang Zheng,Wang Fei,Li Zheng,Ye Zeng,Zhuo Qifeng,Xu Wenyan,Liu Wensheng,Liu Mengqi,Fan Guixiong,Qin Yi,Zhang Yue,Chen Xuemin,Yu Xianjun,Xu Xiaowu,Ji Shunrong
Abstract
Abstract
Background
Although some factors that predict the prognosis in pancreatic neuroendocrine tumor (pNET) have been confirmed, the predictive value of lymph node metastasis (LNM) in the prognosis of pNETs remains conflicting and it is not clear whether regional lymphadenectomy should be performed in all grades of tumors.
Methods
We included pNET patients undergoing surgery in Shanghai pancreatic cancer institute (SHPCI). The risk factors for survival were investigated by the Kaplan–Meier method and Cox regression model. We evaluated the predictors of LNM using Logistic regression.
Results
For 206 patients in the SHPCI series, LNM was an independent prognostic factor for entire cohort suggested by multivariate Cox regression analysis. LNM (P = 0.002) predicted poorer overall survival (OS) in grade 2/3 cohort, but there is no significant association between LNM and OS in grade 1 cohort. Grade (P < 0.001) and size (P = 0.049) predicted LNM in entire cohort. Grade (P = 0.002) predicted LNM while regardless of size in grade 2/3 cohort.
Conclusions
Based on our own retrospective data obtained from a single center series, LNM seems to be associated with poorer outcome for patients with grade 2/3 and/or grade 1 > 4 cm tumors. On the other way, LNM was seems to be not associated with prognosis in patients with grade 1 tumors less than 4 cm. Moreover, tumor grade and tumor size seem to act as independent predictors of LNM. Thus, regional lymphadenectomy should be performed in grade 2/3 patients but was not mandatory in grade 1 tumors < 4 cm. It is reasonable to perform functional sparing surgery for grade 1 patients or propose a clinical-radiological monitoring.
Funder
National Natural Science Foundation of China,China
National Natural Science Foundation of China
Shanghai Municipal Science and Technology Major Project
Scientific Innovation Project of Shanghai Education Committee
Clinical Research Plan of Shanghai Hospital Development Center
Xuhui District Artificial Intelligence Medical Hospital Cooperation Project
Shanghai Municipal Science and Technology Commission
Commission of Health and Family Planning
Publisher
Springer Science and Business Media LLC
Cited by
5 articles.
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